Lifeboat Foundation

Human and animal movements generate slight neural signals from their brain cells. These signals obtained using a neural interface are essential for realizing brain-machine interfaces (BMI). Such neural recording systems using wires to connect the implanted device to an external device can cause infections through the opening in the skull. One method of solving this issue is to develop a wireless neural interface that is fully implantable on the brain.

However, the neural interface implanted on the brain surface should be of small size and minimally invasive. Furthermore, it requires the integration of a power source, antenna for wireless communication, and many functional circuits.

Now, a research team at the Department of Electrical and Electronic Information Engineering at Toyohashi University of Technology has developed a wafer-level packaging technique to integrate a silicon large-scale integration (LSI) chip in a very thin film of a thickness 10 µm (Sensors, “Co-design method and wafer-level packaging technique of thin-film flexible antenna and silicon CMOS rectifier chips for wireless-powered neural interface systems”).

Continue reading “Wirelessly supplying power to brain” »

Now, that’s a concept! Spray paint from a can that harnesses solar energy. Imagine, you can spray paint windows, patio tables, your car, a bike, etc. with Solar Spray Paint in a can; and watch your gadgets get charged. It is almost like the “Computer Screen in the Can” idea that I had last week. Geez, wonder if she could partner with me on that concept?

Researcher aims to engineer spray paint that can convert sun’s elusive energy to electricity.

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A NASA team plans to build the first integrated-photonics modem, using an emerging, potentially revolutionary technology that could transform everything from telecommunications, medical imaging, advanced manufacturing to national defense.

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Stanford University PhD candidate, Song Han, who works under advisor and networking pioneer, Dr. Bill Dally, responded in a most soft-spoken and thoughtful way to the question of whether the coupled software and hardware architecture he developed might change the world.

In fact, instead of answering the question directly, he pointed to the range of applications, both in the present and future, that will be driven by near real-time inference for complex deep neural networks—all a roundabout way of showing not just why what he is working toward is revolutionary, but why the missing pieces he is filling in have kept neural network-fed services at a relative constant.

There is one large barrier to that future Han considers imminent—one pushed by an existing range of neural network-driven applications powering all aspects of the consumer economy and, over time, the enterprise. And it’s less broadly technical than it is efficiency-driven. After all, considering the mode of service delivery of these applications, often lightweight, power-aware devices, how much computation can be effectively packed into the memory of such devices—and at what cost to battery life or overall power? Devices aside, these same concerns, at a grander level of scale, are even more pertinent at the datacenter where some bulk of the inference is handled.

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What if computers could recognize objects as well as the human brain could? Electrical engineers at the University of California, San Diego have taken an important step toward that goal by developing a pedestrian detection system that performs in near real-time (2−4 frames per second) and with higher accuracy (close to half the error) compared to existing systems. The technology, which incorporates deep learning models, could be used in “smart” vehicles, robotics and image and video search systems.

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Another step forward for Quantum — The Quantum Current. US Dept. of Energy has a new method to generate very low-resistance electric (Quantum) current which will improve our methods for energy, quantum computing, and medical imaging, and possibly even a new mechanism for inducing superconductivity—the ability of some materials (zirconium pentatelluride) to carry current with no energy loss.

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Carnegie Mellon University is embarking on a five-year, $12 million research effort to reverse-engineer the brain and “make computers think more like humans,” funded by the U.S. Intelligence Advanced Research Projects Activity (IARPA). The research is led by Tai Sing Lee, a professor in the Computer Science Department and the Center for the Neural Basis of Cognition (CNBC).

The research effort, through IARPA’s Machine Intelligence from Cortical Networks (MICrONS) research program, is part of the U.S. BRAIN Initiative to revolutionize the understanding of the human brain.

Continue reading “CMU announces research project to reverse-engineer brain algorithms, funded by IARPA” »

By now, everyone is probably familiar with holographic performances from such artists as Elvis, Micheal Jackson and the one that started it all, Tupac Shakur at Coachella. However, the real pioneers of performance holograms were that quirky cartoon band, Gorillaz. The costs of a holographic setup would make your toes curl, but the technology itself is fairly straight forward. Projecting onto a specialized screen which is as close to invisible as one can get. There are two main players in the space, Holo-gauze and Musion.

When it comes to digital artists, there is one name that stands out from all others. Hatsune Miku. What makes Miku so unique when compared to holograms of dead celebrities or even the animated Gorillaz with Blur frontman, Damon Albarn, is that she is entirely computer generated. A software instrument manifest as an anime character who has become as much of a ‘real’ celebrity as anyone currently in the charts.

Continue reading “Could Digital Artists Replace Real Artists?” »

As I said this morning; there is something definitely going with Quantum today. Maybe it’s the planet alignment (I saw there was something going on with the alignment with Aquaris today) — this is awesome news.

Rigetti Computing is working on designs for quantum-powered chips to perform previously impossible feats that advance chemistry and machine learning.

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